The background description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventors, to the extent it may be described in this background section, as well as aspects of the description that may not otherwise qualify as prior art at the time of filing, are neither expressly nor impliedly admitted as prior art against the present technology.
Maps, in either printed or digitally displayed form, often show a road as a single line or as two narrowly spaced apart lines. The width of the space or line may or may not be proportional to the actual width of the road. Typically, such maps do not show the number of lanes in the road or additional exit lanes, bicycle lanes, etc. Nor do they illustrate any details of roadway intersections or valid paths that a vehicle is allowed to take when passing through the intersections.
Fully automated driving systems are preferably designed to operate a vehicle on a road without driver interaction or other external control, for example, in self-driving or autonomous vehicles. Advanced driver safety systems monitor the situation of a vehicle, including its location and the location of vehicles in its vicinity. Such systems may require maps that encode both lane-level and roadway intersection information with high degrees of precision. The lane-level and roadway intersection information may be used in a variety of situations, such as for generating a smooth trajectory for path planning, for predicting the behavior of other vehicles, or for planning and/or reasoning proper vehicle behavior at intersections.
In many cases, maps are generated either through a tedious manual annotation process, by driving the exact lane layout with a test vehicle, or by analyzing a collection of GPS tracks. The methods require significant amounts of manual work, either through annotation or for collection.
Accordingly, it would be desirable to provide accurate, detailed intersection maps with less preparation effort.